code: def _create_dataloader(self, batch_size, r, bgs):
      items = ljspeech(c.data_path, "metadata.csv")
      dataset = TTSDataset.MyDataset(
          r,
          c.text_cleaner,
          compute_linear_spec=True,
          ap=self.ap,
          meta_data=items,
          tp=c.characters if "characters" in c.keys() else None,
          batch_group_size=bgs,
          min_seq_len=c.min_seq_len,
          max_seq_len=float("inf"),
          use_phonemes=False,
      )
      dataloader = DataLoader(
          dataset,
          batch_size=batch_size,
          shuffle=False,
          collate_fn=dataset.collate_fn,
          drop_last=True,
          num_workers=c.num_loader_workers,
      )
      return dataloader, dataset
  
file_path: TTS/tests/test_loader.py
imports: import os
  import shutil
  import unittest
  import numpy
  import torch
  from tests import get_tests_input_path, get_tests_output_path
  from torch.utils.data import DataLoader
  from TTS.tts.datasets import TTSDataset
  from TTS.tts.datasets.preprocess import ljspeech
  from TTS.utils.audio import AudioProcessor
  from TTS.utils.io import load_config
label_desc: Use image node_id 2 for calling the TestTTSDataset obj's underlying member method code with example usage: obj._create_dataloader(batch_size, r, bgs) and returns: dataloader,  dataset